Architecture. Even though we often write about novel gene findings in the epilepsies, we assume that most epilepsies are complex genetic or polygenic. Polygenic inheritance suggests the genetic architecture is composed of multiple interacting genetic risk factors, each contributing a small proportion to the disease risk. However, when using the phrase genetic architecture, sometimes I am not quite sure what I actually mean by this. For example, how many genes are needed? This is why I wanted to build a model genetic architecture and explore what happens if we build a genetic disease solely from rare risk variants. Follow me to a brief back-of-the-envelope calculation of how this might work.
Beyond SCN1A. Dravet Syndrome is a severe fever-associated epileptic encephalopathy. While the large majority of patients with Dravet Syndrome carry mutations in the SCN1A gene, the genetic basis is unknown in up to 20% of patients. Some female patients with Dravet-like epilepsies have mutations in PCDH19, but other than this, no additional major gene for typical Dravet Syndrome is known. In a recent paper in Neurology, de novo mutations in GABRA1 and STXBP1 are identified as novel causes for Dravet Syndrome. In addition, several SCN1A-negative patients were shown to have mutations in SCN1A that were initially missed. Continue reading
Program completed. On Sunday, we finished our EuroEPINOMICS next generation sequencing (NGS) bioinformatics meeting. After working through the command line, running scripts, and staring at black screens with white cursors, we completed our four day course by looking at the more user friendly, web-based tools that the NGS world has to offer, including Galaxy, Varbank, and Ingenuity. I think it was the general consensus among the participants that this was the bioinformatics meeting that we needed in order to understand the data that we generate and deal with on day-to-day basis. These were my favorite sound bites of our meeting. Continue reading
FASTA, FASTQ, SAM, BAM, BWA, GC, GATK, IGV. Phew. Day 2 at the EuroEPINOMICS bioinformatics workshop in Leuven. Usually my work starts after the initial NGS raw data quality control and mapping procedures. Today’s topics are supposed to improve my understanding of sequencing analysis and NGS data interpretation. While we are still struggling, other scientists have done their home work already. Here are some of the remarkable publications from this week.
Lessons. Today was the first day of our bioinformatics workshop in Leuven, Belgium. We started out with some basic command line programming and eventually moved on to working with R Studio. What is this all about? It’s about getting some basic understanding of what your computer does and how your computer handles files. It’s about good data and bad data and losing the fear of the command line. We collected responses from the participants today about today’s take home messages. Continue reading
Polygenic. Schizophrenia is a complex neurodevelopmental disorder that is assumed to be caused by a mixture of genetic and non-genetic factors. The genetic component in schizophrenia is thought to be polygenic, i.e. due to the interaction of multiple genetic factors. Rare variants may play a particular role in this presumable polygenic genetic architecture, but so far this component of the genetic morbidity has been hard to pin down. Now, a recent study in Nature explores the role of rare, disruptive mutations in schizophrenia using large-scale population-based exome sequencing. Let’s find out about a new level of exome-wide honesty and why even a gene with 10 disruptive mutations in cases and none in controls is only mentioned in passing. Continue reading
In final week before our EuroEPINOMICS bioinformatics workshop in Leuven people get a little busy and start reading up on all sorts of things. Accordingly, this week’s papers come from all areas of genetics and life science, including three studies in Annals of Neurology on epilepsy genetics.
Sequence first. There are larger genetic studies but not too many. In a recent study in Nature Genetics, roughly 150,000 individuals were genotyped to assess the importance of rare, disruptive variants in SLC30A8 in type 2 diabetes. This genomic tour de force was made possible by available and curated databases that could be tapped to extract the necessary genetic information. Also, this study highlights some of the surprises that we can expect by mining the human genome for disease-related information. Rare, disruptive variants in SLC30A8 protect against type 2 diabetes. Let’s review why these rare, protective genetic factors might be particularly important for biomedical research and what kind of studies we need to identify them. Continue reading
Success rate. What is in an exome? There are lots of rare and unknown variants that are hard to make sense of unless we can ask a specific question or have further data to limit the number of genes that we look at. Genetic studies in recessive diseases with limited candidate genes to consider might represent one of the most straightforward cases. In a recent paper in BMC Neurology, the genetic cause of a recessive epilepsy/intellectual disability syndrome in a consanguineous family presenting with primary microcephaly was solved using a single exome of an affected individual. Was this just lucky or can this strategy be applied to any recessive family with a reasonable chance? Continue reading